Triple
T11893710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interlagos |
E282981
|
entity |
| Predicate | hasCorner |
P42380
|
FINISHED |
| Object | Laranjinha |
E953585
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Laranjinha | Statement: [Interlagos, hasCorner, Laranjinha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laranjinha Context triple: [Interlagos, hasCorner, Laranjinha]
-
A.
Laranjinha
chosen
Laranjinha is a fast, sweeping right-hand bend on the Autódromo José Carlos Pace (Interlagos) circuit in São Paulo, Brazil, known for its challenging, high-speed nature.
-
B.
Barquinha
Barquinha is a Brazilian syncretic religious tradition that incorporates the sacramental use of ayahuasca within a blend of Christian, Afro-Brazilian, and Indigenous spiritual practices.
-
C.
Campinho
Campinho is a small village in the municipality of Reguengos de Monsaraz in Portugal’s Alentejo region.
-
D.
Piquinho
Piquinho is the prominent summit cone at the top of Mount Pico in the Azores, known as the highest point in Portugal.
-
E.
Cajueiro
Cajueiro is a neighborhood within the city of Recife in northeastern Brazil.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8dd1172988190a2c13d37220f2f93 |
completed | April 10, 2026, 11:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f43fe43c7c8190a85d464fd48e00d9 |
completed | May 1, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:44 p.m.